For more than a decade, numerous studies have projected a severe shortage of nurses. Despite the
positive effects of a weak economy on the nurse labor supply, recent analyses indicate the persistence of a significant shortage (Staiger, Auerbach, & Buerhaus, 2012). The U.S. Department of Labor, Bureau of Labor Statistics (2012) projects a need for 1.2 million new nurses by 2020 to meet increasing demands and losses due to
retirement.
In the face of this demand, considerable evidence of a nurse faculty shortage exists, which is expected to worsen over the next decade. A
survey reported by the American Association of Colleges of Nursing indicated that of all budgeted full-time faculty positions in baccalaureate (BSN) and
graduate degree programs, 1,088, or 7.7%, were vacant (Fang & Li, 2012). A telling indicator of the
inadequate supply of faculty are reports that baccalaureate and higher degree programs, as well as associate degree nursing (ADN) programs, turn away
thousands of qualified applicants due to a lack of necessary educational resources. The availability of faculty is one of several interrelated factors
cited in explaining constraints on teaching capacity. In a survey of baccalaureate and higher degree programs, almost two thirds of these nursing schools
identified faculty shortages as a reason for not accepting all qualified applicants into entry-level baccalaureate programs (American Association of Colleges of Nursing, 2012). Other top-cited reasons for not accepting all qualified
applicants were insufficient clinical teaching sites and limited classroom space. A more recent survey by the National League for Nursing (2013) reported that, although the percentage of qualified applicants turned down by ADN programs slightly
decreased from 51% to 45% between 2011 and 2012, the percentage of qualified applicants rejected by BSN programs remained steady at 36% over the same
period.
The faculty shortage has been attributed to a number of causes:
- Demographic characteristics. Nurses generally pursue faculty roles at
an older age than their counterparts in other academic fields (Joynt & Kimball, 2008), and they
typically retire at an early age (62.5 years), resulting in short faculty careers (Berlin & Sechrist,
2002). The average age of nurse faculty with graduate degrees ranged from 50.7 years for assistant professors with a master’s degree to 60.5
years for professors with doctoral degrees (American Association of Colleges of Nursing, 2012).
-
Low salaries. Opportunities in the practice sector that typically offer better compensation may have an adverse effect on the supply of nurse faculty (Yordy, 2006).
- Changing workload demands. Unmet expectations of their roles associated with such
changes may affect faculty satisfaction and commitment (Yordy, 2006), although the evidence related to
faculty workload is not strong and is largely limited to single institutions or regions (Gerolamo & Roemer,
2011).
As part of a larger initiative to address concerns about limited capacity for preparing the nursing workforce and funding
research to evaluate interventions to decrease the nursing faculty shortage (
http://www.EvaluatingInnovationsInNursing.org), the authors conducted a national survey of nurse faculty. The intent was to establish baseline
data about nurse faculty work–life, perceived workload and productivity, and satisfaction with specific aspects of the job. A Web interface (
http://www.evaluatinginnovationsinnursing.org/nufaqs-nurse-faculty-data-query/?intro=Yes) was created for the use of individual nursing programs to
compare their own faculty members with the national averages for programs of similar scope, research intensity, and other salient characteristics on
variables of interest. From the survey, a high level of reported emotional exhaustion was discovered, which is a key component of occupational burnout and
intent to leave academic nursing, both of which are likely to exacerbate the nurse faculty shortage.
The current study examines the contribution of
potentially changeable aspects of work–life to these worrisome outcomes (emotional exhaustion and intent to leave academic nursing). The primary research
question was: How are aspects and perceptions of work–life associated with emotional exhaustion and intent to leave academic nursing? To address this
question, the analyses addressed (a) how faculty members vary on aspects of work–life, as well as other key characteristics of their jobs; and (b) the
relative contribution of these aspects of work–life to each of the outcomes.
Emotional exhaustion and, more broadly, occupational burnout is a
psychological response to chronic stressors in the workplace. It has been shown to have an adverse impact on job performance and negative consequences for
the health and well-being of workers (Cimiotti, Aiken, Sloane, & Wu, 2012; Cropanzano, Rupp, & Byrne, 2003; Hakanen & Schaufeli,
2012; Vahey, Aiken, Sloane, Clarke, & Vargus, 2004; Wright & Cropanzano, 1998) and may contribute to faculty members’ decisions to leave academic nursing. Although substantial
empirical literature exists documenting the negative outcomes of burnout among staff nurses, including the impact on intent to leave and attrition (Aiken, Clarke, Sloane, Sochalski, & Silber, 2002; Flynn, Thomas-
Hawkins, & Clarke, 2009), the prevalence and correlates of burnout among nurse faculty members have not been explored. Awareness of factors
contributing to burnout is essential to identifying potential strategies for prevention, with the aim of ensuring a high-performing faculty workforce.
Studying intent to leave aims to identify the contribution of changeable factors, other than reaching retirement age, that may have a direct impact on
retaining existing faculty members and ultimately on the adequacy of the supply. Taken together, identification of sources of occupational burnout and
factors associated with intent to leave is critical to developing approaches to enhance the supply of nurse faculty members and their capacity to educate
sufficient numbers of nurses with the competencies required in a reformed health care system.
Method
Data Collection
A national survey of a random, stratified sample representative of all full-time faculty was conducted from
October 2010 to May 2011. A two-stage sampling strategy was designed to yield a minimum of 3,000 survey respondents. First, a comprehensive list was
compiled of schools and programs that offered, at a minimum, one prelicensure degree program. The list was assembled using the most recent roster of
prelicensure programs published by the National Council of State Boards of Nursing and supplemented by information compiled by the Association of American
Colleges of Nursing and the directories of the National League for Nursing Accrediting Commission and the Commission on Collegiate Nursing Education. From
this list, a sample was selected that was proportionally representative of all programs in the United States by prelicensure degree (ADN or BSN) offered,
urbanization (urban or rural), and research intensity (defined as residing in a doctoral-granting institution or not, adopted from the Carnegie
Classification System [Carnegie Foundation for the Advancement of Teaching, 2009]). Information for
stratifying the sample was gathered from the database of the National Center for Education Statistics and the Carnegie Classification dataset. Using
standard survey procedures, the sample was drawn in replicates (i.e., smaller subsets, each of which was representative and stratified as noted previously)
to monitor responses to ensure a yield of 3,000 faculty members.
Second, rosters were compiled of full-time faculty at these randomly selected
schools, and the accuracy of each school’s roster was confirmed with the respective dean’s office. All full-time faculty members (n = 3,975)
teaching in undergraduate or graduate programs or both at the selected schools were invited to participate. Questionnaires, administered by mail and e-
mail, with telephone follow-up, were completed by 3,120 faculty members, for a response rate of 78.5% from 269 schools. Prior to data collection, the
research was approved by the Institutional Review Board at Rutgers University. Only respondents with no missing data on variables in the regression models
were included in the analyses.
Measures
Emotional Exhaustion. To measure emotional exhaustion, the
emotional exhaustion (EE) subscale from the Maslach Burnout Inventory (MBI) was used, which is a standard measure of occupational burnout that has been
extensively validated in multiple disciplines (Maslach, Jackson, & Leiter, 1996). Of the three
subscales composing the MBI (the other two are depersonalization and personal accomplishment), the EE scale has been established theoretically and
empirically as measuring the core element of burnout (Kallaith, O’Driscoll, Gillespie, & Bluedorn, 2000
; Koeske & Koeske, 1993; Lee & Ashforth, 1993
; Leiter, 1993; Reilly, 1994). Maslach (2003) described emotional exhaustion as emotional overload that is characterized by feelings of being
drained and used up by one’s work and lacking energy to face another day. To reduce respondent burden, three of the nine items composing the EE subscale
were used. Principal component analyses were conducted of responses to all nine items in an existing dataset, consisting exclusively of nurse faculty,
which were collected but not analyzed for a broader study of RNs (Flynn, Liang, Dickson, & Aiken, 2010
). Consistent with Maslach’s theory, the three items representing feelings of being drained, feelings of being used up, and lack of energy were
identified as those that best predict the overall nine-item score (ranging from 0 to 54, using a Likert-type, 7-point response scale in which 0 =
never and 6 = every day). The aim was to approximate the MBI-EE subscale to apply Maslach’s criteria for differentiating faculty members
reporting high levels of emotional exhaustion from those reporting average or low levels. That threshold (>27 on a score of 0 to 54 among workers in the
health professions) has been demonstrated by numerous studies to identify individuals who are at risk for adverse health consequences and diminished
capacity to perform their jobs (Cimiotti et al., 2012; Cropanzano
et al., 2003; Hakanen & Schaufeli, 2012; McHugh,
Kutney-Lee, Cimiotti, Sloane, & Aiken, 2011; Wright & Cropanzano, 1998).
To
approximate the Maslach MBI-EE scale using the three items, an adjustment ratio was calculated by dividing the mean of the nine items by the mean of the
three items, which was then applied to the data; 38.8% of faculty members were classified as reporting high levels of emotional exhaustion, according to
Maslach’s criteria. To provide validation of this adjustment strategy, a larger existing data set was used of more than 14,000 RNs working in varied
settings who were randomly sampled and surveyed in a study of the effects of work environments on performance outcomes (Flynn et al., 2010). The adjustment ratio was then applied to estimate the average total score; the estimated score was 19.6, compared
with the actual score of 19.4, for a difference of 1%. In addition, in calculating an adjustment ratio based on the validation sample and applying it to
the data, 38.8% of faculty members were classified as having high emotional exhaustion, which is identical to the percentage designated by using the ratio
calculated with the current study data.
Intent to Leave Academic Nursing. Faculty members were asked how likely they were to leave teaching in
the next 5 years, using a 4-point response scale (1 = very likely, 2 = somewhat likely, 3 = somewhat unlikely, 4 = very
unlikely). For the dependent variable, the responses were dichotomized (somewhat or very likely to leave, contrasted with somewhat
or very unlikely).
Domains of Predictors. A comprehensive set of factors was incorporated to predict emotional exhaustion and intent to
leave academic nursing in the current study models. The following variables were selected to capture spheres of influence having varying levels of
specificity to the respondent’s role as a nurse faculty member:
Demographic and background factors that are generally
established prior to entry into the profession, including age, gender, race/ethnicity, and highest nursing degree as currently reported (78% of respondents
earned their highest nursing degree prior to accepting a full-time faculty position).
Characteristics of the respondent’s institution that
affect all of those employed there (whether they teach at a school offering an ADN or BSN degree, research intensity of the school, and urban/rural
locale).
Characteristics of the respondent’s particular job and status (rank, tenure status, whether he or she is teaching in a
postbaccalaureate program, extent of administrative responsibilities, salary).
Their reported performance in their role, including workload
(number of hours per week devoted to all work activities, service on school or departmental committees) and productivity (development of new courses,
revising courses, conversion to online format, number of articles publications, preparation of grant applications).
Perceptions of the
adequacy of their work and role (dissatisfaction with aspects of work–life).
Health status, which may be affected by factors from all
levels.
Within each domain, those items that were significantly related to the outcome variables in bivariate analyses (p <
0.05) were retained in the analysis. In a few cases, the variables were included for conceptual completeness, whether or not they met the bivariate
criterion (e.g., the institutional characteristics that served as stratifying variables in the sampling).
Suited to the focus of the analysis,
particular attention was devoted to the fifth domain (i.e., perceptions of the adequacy of their work and role). Items were developed that reflect the
terms and conditions of work (e.g., salary, workload, job security, availability of resources), as well as the content of work (e.g., meaningfulness,
autonomy and independence, rewards for innovation). Respondents rated satisfaction with each (very satisfied, somewhat satisfied, somewhat
dissatisfied, very dis-satisfied). None of the items retained in the analysis were inter-correlated at a level of 0.60 or higher. Table 1 and the Figure provide details on all
predictors.
Analysis
To identify
factors associated with emotional exhaustion and intent to leave academic nursing, logistic regression models were estimated for each of these dependent
variables using Stata statistical software. Stata svyset and svy commands were used to adjust for complex design effects (i.e., clustering due to the two-
stage sampling procedure and stratification).
Findings
As presented in Table 1, the age of faculty members averaged 51.4 years; 15.8% were within 5 years of retirement (age 66
years), 95% were women, 88% were White, and 19.7% held a doctorate as their highest degree, whereas 70.6 % held a master’s degree. Although 28.6% were
tenured and 20.8% were on a tenure track but not yet tenured, the majority were either at an institution that did not offer tenure (26.2%) or they were not
on a tenure track (24.4%). Slightly more than one third were either full or associate professors, whereas almost two thirds occupied junior ranks.
Regarding type of school, 46.2% taught at schools offering an ADN degree, whereas 53.8% taught in schools offering a BSN; almost one quarter worked at
research-intensive institutions, and 78.6% taught at schools located in urban areas, with the remaining 21.4% working in locales classified as rural or
small towns. Regarding type of program within the schools, 76% taught exclusively in prelicensure degree programs, whereas 24% taught in graduate degree
programs. Total reported workload averaged 48.3 hours per week. Regarding productivity during the previous year, 19.8% of faculty members reportedly
published one or more articles in peer-reviewed journals, 28.3% prepared one or more grant proposals, and 34.2% significantly revised two or more
courses.
More than 80% of faculty members were somewhat or very satisfied with their work overall (
Figure). The most prominent sources of dissatisfaction were availability of travel funds (52.7% reported very dissatisfied or
somewhat dissatisfied), salary (50.8%), and workload (32.0%). Between 20% and 30% of faculty members were dissatisfied with the direction of their
department or school, the availability of technology support, their relationship with their school administration, the flexibility to balance work and
family life, teaching support, and benefits. Regarding the outcomes assessed in our analyses (Table 2
), 38.8% of faculty members reported high levels of emotional exhaustion, and 32% indicated that they were likely to leave academic nursing in the next
5 years. By age, two thirds of faculty members who would be of retirement age in 5 years (currently 61 years or older) intended to leave; 30.9% of those
currently aged 51 to 60 years intended to leave, and slightly more than 20% in the younger age groups were similarly inclined.
Predictors of
Emotional Exhaustion
As shown in Table 3, major significant predictors of emotional
exhaustion were dissatisfaction with workload (odds ratio [OR] = 1.82), devoting 50% or more time to administrative responsibilities (OR =
1.73), dissatisfaction with flexibility to balance work and family life (OR = 1.58), reporting fair or poor health status (OR = 1.46),
dissatisfaction with the meaningfulness of work (OR = 1.36) and with the direction of the department or school (OR = 1.27), and time spent on
all work activities (OR = 1.02). For example, an increase in total workload from 40 to 50 hours per week was associated with 22% higher odds of
emotional exhaustion.
To assess the proportion of variance in emotional exhaustion explained by the current study’s
model (R2) and the relative contribution of various facets of work–life, a linear regression model was also estimated, with a continuous
version of the emotional exhaustion score as the dependent variable (calculated as the total score based on the 0 to 6 response to each item of the scale).
Predictors were entered in six blocks (Table A; available in the online version of this article).
The content of the six blocks is the same as in Table 3; however, the order of entry of the
blocks reflects the level of specificity of the domains of variables to the faculty member’s particular role (as described more fully previously)
—individual characteristics, institution characteristics, job characteristics, reported workload and productivity, dissatisfaction with aspects of
work–life, and health status. The model accounted for 40% of the variation in emotional exhaustion (R2 = 0.40). Upon entry into the
model, dissatisfaction with elements of work–life accounted for 28% of the variation in emotional exhaustion, 7% was explained by reported workload and
productivity, 2% was accounted for by job characteristics, 2% by health status, and 1% by other individual characteristics; institution characteristics did
not contribute to emotional exhaustion in the estimated model.
Predictors of Intent to Leave Academic Nursing
Several factors significantly predicted faculty members’ intent to leave academic nursing within the next 5 years (Table 4)—age within 5 years of retirement (OR = 6.41), having a BSN (OR = 2.70) or MSN (
OR = 1.91) as the highest nursing degree earned, not holding tenure in an institution that offers tenure (OR = 1.49); years full-time on a
faculty (each additional year was associated with a 6% added likelihood of leaving); not working on an advanced nursing degree (OR = 1.59); being
certified as an advanced practice nurse (OR = 1.56); reporting high emotional exhaustion (OR = 1.27); and dissatisfaction with availability
of teaching support (OR = 1.19), workload (OR = 1.26), salary (OR = 1.18) and rewards for innovation on the job (OR = 1.16).
The model was estimated, removing respondents who were within 5 years of retirement, and the results were essentially the same, except that assistant
professors were slightly less likely to intend to leave.
To assess the proportion of variance explained, a linear regression model was estimated with intent to leave as a 4-point
ordinal measure (not shown) and an order of entry, reflecting the same conceptualization as the model of emotional exhaustion. In this model, 11.5% of the
variation in intent to leave was accounted for by age, and another 14% was explained by other domains in the model; chief among them were dissatisfaction
with aspects of work–life (8.4%), job characteristics and status (4%), and reported workload and productivity (1%).
Discussion
Overall job satisfaction among nurse faculty members was high (86.8% reported that they were very satisfied or somewhat satisfied),
which is similar to the levels reported in surveys of faculty in other fields (National Center for Education
Statistics, Institute of Education Sciences, 2004). Those aspects of work that commanded the greatest dissatisfaction (exceeding 20%) generally
coalesced around working conditions (e.g., the highest levels were associated with material rewards and resources, including salary, workload, benefits,
funds for travel, and technology support). The two exceptions were moderate levels of dissatisfaction with the direction of the school (27.3%) and with
their relationship with school administration (23.2%).
Notably, levels of emotional exhaustion were high (39%), exceeding those reported in studies
of nurses in clinical roles, which were 34% among nurses in hospitals and 37% among those working in nursing homes (McHugh et al., 2011). The rates of emotional exhaustion among nurse faculty members in the current study were also higher than those
reported in a single-site study of academic medical faculty (Shanafelt et al., 2009), which established
that 30.2% of faculty physicians in a department of internal medicine reported high emotional exhaustion scores. High levels of emotional exhaustion
foretell stress-related problems for individual nurse faculty members and possibly suboptimal functioning in the classroom. Important to faculty retention
rates, the current study findings indicate that high emotional exhaustion was independently associated with intent to leave academic nursing (Table 4).
The rate of intent to leave academic nursing among those faculty who were of preretirement
age is alarming, given the shortage in nurse faculty supply and the implications of that shortage for meeting the nation’s health care needs. Almost one
third of current faculty members aged 51 to 60 years and one fifth of those 50 years or younger intend to leave academic nursing within 5 years.
Predictors of Emotional Exhaustion and Intent to Leave Academic Nursing
Although overall job satisfaction was high, those
faculty members who registered dissatisfaction with specific elements of work–life were more likely to report high emotional exhaustion and an intent to
leave academic nursing within 5 years. Most important among work–life predictors of emotional exhaustion were dissatisfaction with workload and flexibility
to balance work and family life, followed by negative assessments of the meaningfulness of work and the direction of the department or school. With respect
to intent to leave academic nursing, the contribution of aspects of work–life was approximately equal to that of proximity to retirement age, and material
concerns played a prominent role; dissatisfaction with workload, salary, and availability of teaching support were significant predictors, as was emotional
exhaustion. Interestingly, those nonmaterial dimensions of work–life that garnered the highest rates of dissatisfaction—the direction of the department or
school and relationship with the school administration—were not significant predictors of intent to leave academic nursing. It is conceivable that such
nonmaterial dimensions may be associated with intent to leave the current employer, rather than leave the field, which is a prospect that merits further
research attention. Although job turnover may not directly affect the numbers of faculty members in the field, the associated disruption may affect
teaching productivity.
The extent to which perceptions of burden accounted for emotional exhaustion, as well as intent to leave, is particularly
worrisome. Recommendations of recent high-profile commissions, such as the Institute of Medicine’s reports on the future of nursing (Institute of Medicine, 2010) and the needs of older Americans (
Institute of Medicine, 2008) as well as provisions of the federal health reform legislation (Patient
Protection and Affordable Care Act, 2010) call for educating more nurses and preparing them to play a broader spectrum of roles in our health
care delivery system (e.g., establishing nurse-managed community health centers, providing primary care to newly insured populations, leading
interprofessional collaborations). Preparing the nurse workforce with the expertise for assuming these roles will intensify the pressures on existing
faculty capacity, adding to those very burdens that contribute to the current nurse faculty shortage and undermine commitment to teach. A clear need exists
to address faculty workload and working conditions and to monitor faculty perspectives on those elements of work–life that are associated with emotional
exhaustion and intent to leave as identified in this article. A Web interface to the data of the predictors analyzed in the current study is publicly
available for individual nursing programs to compare their own faculty members with national averages. The questionnaire can be downloaded to collect
similar data from faculty in individual programs. The data interface from the current study can be customized for programs of similar scope, research
intensity, and other key characteristics to facilitate meaningful comparisons (
http://www.evaluatinginnovationsinnursing.org/nufaqs-nurse-faculty-data-query/?intro=Yes).
The finding that faculty members with advanced
practice nurse certification (APRNs) were 1.5 times more likely to express an intention to leave teaching is disconcerting. The projected increase in
demand for primary care services associated with implementation of the Affordable Care Act has been accompanied by growing recognition that APRNs can make
a significant contribution to meeting that need. Without faculty members with APRN certification, the capacity to prepare APRNs will be severely
constrained. More knowledge of the particular needs of this subgroup of faculty may be helpful to the efforts of recruiting and retaining them.
Strategies for Change
Although strategies to increase teaching capacity are widely considered to address the faculty
shortage (Joynt & Kimball, 2008), these approaches may inadvertently contribute to high rates of
faculty exhaustion and may exacerbate faculty shortages. Efforts to enhance faculty capacity must take into account the likely impact on faculty workload
and work–life; yet, most of these strategies have lacked systematic evaluation (Wyte-Lake, Tran, Bowman, Needleman,
& Dobalian, 2013). Acknowledging the importance of generating sound evidence of the effectiveness of such approaches in addressing the
faculty shortage, the Robert Wood Johnson Foundation established a national program, Evaluating Innovations in Nursing Education, to support studies of the
impact of these strategies on teaching productivity, faculty work–life, and the quality of nursing education. Evaluation researchers in collaboration with
nursing programs around the country are completing controlled evaluations of innovations focused on increasing faculty teaching productivity and
efficiency. These initiatives, described below, offer promise in addressing teaching capacity, without aggravating those elements of work–life associated
with the negative outcomes studied in this work.
- Collaborations among educational programs and delivery organizations designed to better align
health system resources with the clinical education needs of students (dedicated education units [DEUs]). DEUs may reduce the stress on academic faculty of
supervising care of patients in delivery settings in which they have little or no standing.
- Reliance on clinical simulation to make more effective
use of instructional expertise and technology to improve student learning. Extensive use of clinical simulation may reduce the workload of academic faculty
by delegating clinical skills evaluation to staff specialists who use clinical scenarios and highfidelity technology to assess students’ clinical
competencies.
- Development of a single baccalaureate curriculum among a regional or statewide consortium of nursing education programs to make more
efficient use of faculty resources and accelerate student progression. Participation in an academic consortium facilitates sharing of faculty to reduce
course loads and also promotes collaboration with colleagues in developing shared course materials, thus potentially reducing preparation time for
individual faculty.
Other projects supported by Evaluating Innovations in Nursing Education address strategies for increasing the supply of
doctorally prepared nurses and aim to increase our understanding of students’ decision making about pursuing doctoral education and faculty careers. These
include:
- Implementation of policies offering incentives for graduate-prepared nurses to pursue faculty careers. These support-for-service programs
may contribute to lowering faculty vacancy rates and commensurate decreases in faculty course load.
- Analyses of factors influencing career choice
among current doctoral students in nursing, stages of decision making leading to a career in nursing education, and prospects of early-entry doctoral
programs for increasing the capacity of nurse faculty.
Findings from these studies, which are intended to inform strategies for increasing
the numbers of new faculty members, will be available in the coming months (Robert Wood Johnson Foundation,
2014).
Limitations of the Study
The cross-sectional design of the current study limits the
ability to discern causal relationships. Following a panel of nurse faculty members over time would facilitate identification of those who actually leave
academic nursing and would also provide more refined analyses of factors that contribute to this outcome. Predictors in the analyses were deliberately
confined to variables associated with work in academic settings. Consideration of factors in other job sectors that may attract academic faculty members
was beyond the purview of this study. More definitive understanding of the impact of seemingly changeable aspects of faculty work–life on teaching
productivity is critical to assuring faculty capacity to educate an adequate supply of nurses to meet future health care needs.
Conclusion
Major contributors to burnout were dissatisfaction with workload and perceived inflexibility to balance work and
family life. Intent to leave was explained, not only by age but also by several potentially modifiable aspects of work, including dissatisfaction with
workload, salary, and availability of teaching support. Preparing sufficient numbers of nurses to meet future health needs will require addressing those
aspects of work–life that undermine faculty teaching capacity.
References
- Aiken, L.H., Clarke, S.P., Sloane, D.M., Sochalski, J. & Silber, J.H. (2002). Hospital nurse staffing and patient mortality,
nurse burnout, and job dissatisfaction. JAMA, 288, 1987–1993. doi:10.1001/jama.288.16.1987 [CrossRef]
- American Association of Colleges of
Nursing. (2012). Nursing faculty shortage fact sheet. Retrieved from
http://www.aacn.nche.edu/media-relations/fact-sheets/nursing-faculty-shortage
- Berlin, L.E.
& Sechrist, K.R. (2002). The shortage of doctorally prepared nursing faculty: A dire situation. Nursing Outlook, 50, 50–56.
doi:10.1067/mno.2002.124270 [CrossRef]
- Carnegie Foundation for the Advancement of Teaching. (2009). The Carnegie classifications of institutions of higher education.
Retrieved from http://classifications.carnegiefoundation.org/
- Cimiotti, J.P., Aiken, L.H., Sloane, D.M. & Wu, E.S. (2012). Nurse staffing, burnout, and health
care-associated infection. American Journal of Infection Control, 40, 486–490. doi:10.1016/j.ajic.2012.02.029 [CrossRef]
- Cropanzano, R., Rupp, D.E. &
Byrne, Z.S. (2003). The relationship of emotional exhaustion to work attitudes, job performance, and organizational citizenship behaviors. Journal of
Applied Psychology, 88, 160–169. doi:10.1037/0021-9010.88.1.160
[CrossRef]
- Fang, D. & Li, Y. (2012). Special survey on vacant faculty positions for
academic year 2011–2012. Retrieved from
http://www.aacn.nche.edu/leading-initiatives/research-data/vacancy11.pdf
- Flynn, L., Liang,
Y., Dickson, G.L. & Aiken, L.H. (2010). Effects of nursing practice environments on quality outcomes in nursing homes. Journal of the American
Geriatrics Society, 58, 2401–2406. doi:10.1111/j.1532-5415.2010.03162.x [CrossRef]
- Flynn, L., Thomas-Hawkins, C.
& Clarke, S.P. (2009). Organizational traits, care processes, and burnout among chronic hemodialysis nurses. Western Journal of Nursing
Research, 31, 569–582. doi:10.1177/0193945909331430 [CrossRef]
- Gerolamo, A.M. & Roemer, M.S. (2011). Workload and the nurse faculty shortage: Implications for
policy and research. Nursing Outlook, 59, 259–265. doi:10.1016/j.outlook.2011.01.002 [CrossRef]
- Hakanen, J.J. & Schaufeli,
W.B. (2012). Do burnout and work engagement predict depressive symptoms and life satisfaction? A three-wave seven-year prospective study. Journal of
Affective Disorders, 141, 415–424. doi:10.1016/j.jad.2012.02.043
[CrossRef]
- Institute of Medicine. (2008). Retooling for an aging America: Building the
health care workforce. Washington, DC: National Academies Press. Retrieved from http://books.nap.edu/openbook.php?record_id=12089
- Institute of Medicine. (2010). The Future of nursing: Leading change, advancing health. Washington, DC: National Academies
Press.
- Joynt, J. & Kimball, B. (2008). Blowing open the bottleneck: Designing new
approaches to increase nurse education capacity. Retrieved from http://www.rwjf.org/content/dam/farm/reports/reports/2008/rwjf29362
- Kallaith, T.J., O’Driscoll, M.P., Gillespie, D.F. & Bluedorn, A.C. (2000). A test of the Maslach
Burnout Inventory in three samples of healthcare professionals. Work & Stress, 14, 35–50. doi:10.1080/026783700417212 [CrossRef]
- Koeske, G.F. & Koeske, R.D.
(1993). A preliminary test of a stress-strain-outcome model for reconceptualizing the burnout phenomenon. Journal of Social Service Research,
17, 107–135. doi:10.1300/J079v17n03_06 [CrossRef]
- Lee, R. & Ashforth, B. (1993). A further examination of managerial burn-out: Toward an integrated
model. Journal of Organizational Behavior, 14, 3–20. doi:10.1002/job.4030140103 [CrossRef]
- Leiter, M. (1993). Burnout as a
developmental process: Consideration of models. In Schaufeli, W., Maslach, C. & Marek, T. (Eds.), Professional burnout: Recent developments in
theory and research (pp. 237–250). Washington, DC: Taylor & Francis.
- Maslach, C. (2003).
The cost of caring. Cambridge, MA: Malor Books.
- Maslach, C., Jackson, S. & Leiter,
M. (1996). Maslach burnout inventory manual. Palo Alto, CA: Consulting Psychologists Press.
- McHugh, M.D., Kutney-Lee, A., Cimiotti, J.P., Sloane, D.M. & Aiken, L.H. (2011). Nurses’ widespread job dissatisfaction, burnout, and
frustration with health benefits signal problems for patient care. Health Affairs, 30, 202–210. doi:10.1377/hlthaff.2010.0100 [CrossRef]
- National Center
for Education Statistics, Institute of Education Sciences. (2004). National study of postsecondary faculty. Retrieved from http://nces.ed.gov/surveys/nsopf/design.asp
- National League for Nursing. (2013). Percentage of qualified applications that were rejected by program type: 2010 to 2012. Retrieved
from http://www.nln.org/research/slides/index.htm
- Patient Protection and Affordable Care Act, 42 U.S.C. § 18001 (2010). Retrieved from
http://frwebgate.access.gpo.gov/cgi-bin/getdoc.cgi?dbname=111_cong_bills&docid=f:h3590enr.txt.pdf
- Reilly, N. (1994). Exploring a paradox: Commitment as a moderator of the stress-burnout relationship. Journal of Applied Psychology,
24, 397–414. doi:10.1111/j.1559-1816.1994.tb00589.x [CrossRef]
- Robert Wood Johnson Foundation. (2014). Evaluating innovations in nursing education.
Retrieved from http://www.evaluatinginnovationsinnursing.org
- Shanafelt, T.D., West, C.P., Sloan, J.A., Novotny, P.J., Poland, G.A., Menaker, R. & Dyrbye,
L.N. (2009). Career fit and burnout among academic faculty. Archives of Internal Medicine, 169, 990–995. doi:10.1001/archinternmed.2009.70 [CrossRef]
- Staiger,
D.O., Auerbach, D.I. & Buerhaus, P.I. (2012). Registered nurse labor supply and the recession—Are we in a bubble?New England Journal of
Medicine, 366, 1463–1465. doi:10.1056/NEJMp1200641 [CrossRef]
- U.S. Department of Labor, Bureau of Labor Statistics. (2012). Economic news release: Table 10. The 30
occupations with the largest projected number of total job openings due to growth and replacements, 2010–20. Retrieved from http://www.bls.gov/news.release/ecopro.t10.htm
- Vahey, D.C., Aiken, L.H., Sloane, D.M., Clarke, S.P. & Vargas, D. (2004). Nurse burnout and patient satisfaction, Medical
Care, 42, 57–66. doi:10.1097/01.mlr.0000109126.50398.5a
[CrossRef]
- Wright, T.A. & Cropanzano, R. (1998). Emotional exhaustion as a predictor of
job performance and voluntary turnover. Journal of Applied Psychology, 83, 486–493. doi:10.1037/0021-9010.83.3.486 [CrossRef]
- Wyte-Lake, T., Tran, K., Bowman,
C.C., Needleman, J. & Dobalian, A. (2013). A systematic review of strategies to address the clinical nursing faculty shortage. Journal of Nursing
Education, 52, 245–252. doi:10.3928/01484834-20130213-02 [CrossRef]
- Yordy, K.D. (2006). The nurse faculty shortage: a crisis for health care. A report to the
Robert Wood Johnson Foundation. Retrieved from
http://www.rwjf.org/content/dam/web-assets/2006/04/the-nursing-faculty-shortage